Connectome
Research Papers
Showing 6 of 7Functional connectome mediates the association between sleep disturbance and mental health in preadolescence: A longitudinal mediation study
Sleep disturbance is known to be associated with various mental disorders and often precedes the onset of mental disorders in youth. Given the increasingly acknowledged bidirectional influence between sleep disturbance and mental disorders, we aim to identify a shared neural mechanism that underlies sleep disturbance and mental disorders in preadolescents. We analyzed a dataset of 9,350 9-10 year-old children, among whom 8,845 had 1-year follow-up data, from the Adolescent Brain Cognitive Development (ABCD) study. Linear mixed-effects models, mediation analysis, and longitudinal mediation analysis were used to investigate the relationship between sleep disturbance, mental disorders, and resting-state network connectivity. Out of 186 unique connectivities, the effect of total sleep disturbance (TSP, from Sleep Disturbance Scale) and mental problems (MP, from Child Behavior Checklist) converged in the default mode network (DMN) and the dorsal attention network (DAN). Within- and between-network connectivities (DMN-DAN, DMN-DMN, DAN-DAN) mediated the relationship between baseline TSD and MP at 1-year follow-up and the relationship between baseline MP and TSD at 1-year follow-up. The pathway model in which sleep disturbance and mental problems affect each other through two anticorrelated brain networks (DMN and DAN) suggests a common neural mechanism between them. Longitudinally, a less segregated DMN and DAN is associated with negative outcomes on mental well-being and sleep disturbance a year later. These findings have important implications for the design of prevention and neurofeedback intervention for mental disorders and sleep problems.
View Full Paper →Interacting brains coming in sync through their minds: an interbrain neurofeedback study
Neurophysiological evidence shows that interpersonal action coordination is accompanied by interbrain synchronization (IBS). However, the functional significance of this association remains unclear. Using two experimental designs, we explored whether IBS is amenable to neurofeedback (NFB). Feedback was provided either as two balls approaching each other (so-called ball design), or as two pendula, each reflecting the oscillatory activity of one of the two participants (so-called pendulum design). The NFB was provided at delta (i.e., 2.5 Hz) and theta (i.e., 5 Hz) electroencephalography frequencies, and manipulated by enhanced and inverse feedback. We showed that the participants were able to increase IBS by using NFB, especially when it was fed back at the theta frequency. Apart from intra- and interbrain coupling, other oscillatory activities (e.g., power spectral density, peak amplitude, and peak frequency) also changed during the task compared with the rest. Moreover, all the measures showed specific correlations with the subjective postsurvey item scores, reflecting subjective feeling and appraisal. We conclude that the use of IBS for NFB might help in specifying the contribution of IBS to interpersonal action coordination and in providing important information about the neural mechanisms of social interaction and the causal dimension of IBS.
View Full Paper →Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training
Neurofeedback (NF) aptitude, which refers to an individual's ability to change brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical applications to screen patients suitable for NF treatment. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude, independent of NF-targeting brain regions. We combined the data from fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the multiple regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Subsequently, the reproducibility of the prediction model was validated using independent test data from another site. The identified FC model revealed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting that NF aptitude may be involved in the attentional mode-orientation modulation system's characteristics in task-free resting-state brain activity.
View Full Paper →Just a very expensive breathing training? Risk of respiratory artefacts in functional connectivity-based real-time fMRI neurofeedback
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI NFB) is a promising method for targeted regulation of pathological brain processes in mental disorders. But most NFB approaches so far have used relatively restricted regional activation as a target, which might not address the complexity of the underlying network changes. Aiming towards advancing novel treatment tools for disorders like schizophrenia, we developed a large-scale network functional connectivity-based rtfMRI NFB approach targeting dorsolateral prefrontal cortex and anterior cingulate cortex connectivity with the striatum. In a double-blind randomized yoke-controlled single-session feasibility study with N = 38 healthy controls, we identified strong associations between our connectivity estimates and physiological parameters reflecting the rate and regularity of breathing. These undesired artefacts are especially detrimental in rtfMRI NFB, where the same data serves as an online feedback signal and offline analysis target. To evaluate ways to control for the identified respiratory artefacts, we compared model-based physiological nuisance regression and global signal regression (GSR) and found that GSR was the most effective method in our data. Our results strongly emphasize the need to control for physiological artefacts in connectivity-based rtfMRI NFB approaches and suggest that GSR might be a useful method for online data correction for respiratory artefacts.
View Full Paper →Using connectivity-based real-time fMRI neurofeedback to modulate attentional and resting state networks in people with high trait anxiety
High levels of trait anxiety are associated with impaired attentional control, changes in brain activity during attentional control tasks and altered network resting state functional connectivity (RSFC). Specifically, dorsolateral prefrontal cortex to anterior cingulate cortex (DLPFC - ACC) functional connectivity, thought to be crucial for effective and efficient attentional control, is reduced in high trait anxious individuals. The current study examined the potential of connectivity-based real-time functional magnetic imaging neurofeedback (rt-fMRI-nf) for enhancing DLPFC - ACC functional connectivity in trait anxious individuals. We specifically tested if changes in DLPFC - ACC connectivity were associated with reduced anxiety levels and improved attentional control. Thirty-two high trait anxious participants were assigned to either an experimental group (EG), undergoing veridical rt-fMRI-nf, or a control group (CG) that received sham (yoked) feedback. RSFC (using resting state fMRI), anxiety levels and Stroop task performance were assessed pre- and post-rt-fMRI-nf training. Post-rt-fMRI-nf training, relative to the CG, the EG showed reduced anxiety levels and increased DLPFC-ACC functional connectivity as well as increased RSFC in the posterior default mode network. Moreover, in the EG, changes in DLPFC - ACC functional connectivity during rt-fMRI-nf training were associated with reduced anxiety levels. However, there were no group differences in Stroop task performance. We conclude that rt-fMRI-nf targeting DLPFC - ACC functional connectivity can alter network connectivity and interactions and is a feasible method for reducing trait anxiety.
View Full Paper →Real-time fMRI amygdala neurofeedback positive emotional training normalized resting-state functional connectivity in combat veterans with and without PTSD: a connectome-wide investigation
Self-regulation of brain activation using real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) is an emerging approach for treating mood and anxiety disorders. The effect of neurofeedback training on resting-state functional connectivity warrants investigation as changes in spontaneous brain activation could reflect the association between sustained symptom relief and brain alteration. We investigated the effect of amygdala-focused rtfMRI-nf training on resting-state functional connectivity in combat veterans with and without posttraumatic stress disorder (PTSD) who were trained to increase a feedback signal reflecting left amygdala activity while recalling positive autobiographical memories (Zotev et al., 2018). The analysis was performed in three stages: i) first, we investigated the connectivity in the left amygdala region; ii) next, we focused on the abnormal resting-state functional connectivity identified in our previous analysis of this data (Misaki et al., 2018); and iii) finally, we performed a novel data-driven longitudinal connectome-wide analysis. We introduced a longitudinal multivariate distance matrix regression (MDMR) analysis to comprehensively examine neurofeedback training effects beyond those associated with abnormal baseline connectivity. These comprehensive exploratory analyses suggested that abnormal resting-state connectivity for combat veterans with PTSD was partly normalized after the training. This included hypoconnectivities between the left amygdala and the left ventrolateral prefrontal cortex (vlPFC) and between the supplementary motor area (SMA) and the dorsal anterior cingulate cortex (dACC). The increase of SMA-dACC connectivity was associated with PTSD symptom reduction. Longitudinal MDMR analysis found a connectivity change between the precuneus and the left superior frontal cortex. The connectivity increase was associated with a decrease in hyperarousal symptoms. The abnormal connectivity for combat veterans without PTSD - such as hypoconnectivity in the precuneus with a superior frontal region and hyperconnectivity in the posterior insula with several regions - could also be normalized after the training. These results suggested that the rtfMRI-nf training effect was not limited to a feedback target region and symptom relief could be mediated by brain modulation in several regions other than in a feedback target area. While further confirmatory research is needed, the results may provide valuable insight into treatment effects on the whole brain resting-state connectivity.
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